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In modern manufacturing there is the trend of the development of the Computer Integrated Manufacturing (CIM). CIM is computerized integration of the manufacturing activities (Design, Planning, Scheduling and Control) which produces right product(s) at right time to react quickly to the global competitive market demands. The productivity of CIM is highly depending upon the scheduling of Flexible Manufacturing System (FMS). Machine idle time can be decreased by sorting the make span which results in the improvement in CIM productivity. Conventional methods of solving scheduling problems based on priority rules still result schedule, sometimes with idle times. To optimize these, this papers model the problem of a flow shop scheduling with the objective of minimizing the makes pan. The work proposed here deal with the production planning problem of a flexible manufacturing system. The objective is to minimize the make span of batch-processing machines in a flow shop. The processing times and the sizes of the jobs are known and nonidentical. The machines can process a batch as long as its capacity is not exceeded. The processing time of a batch is the longest processing time among all the jobs in that batch. The problem under study is NP-hard for makespan objective. Consequently, comparisons based on Gupta’s heuristics, Palmer’s heuristics are proposed in this work. Gantt chart is generated to verify the effectiveness of the proposed approaches.
— Production scheduling is generally considered to be the one of the most significant issue in the planning and operation of a manufacturing system. Better scheduling system has significant impact on cost reduction, increased productivity, customer satisfaction and overall competitive advantage. In addition, recent customer demand for high variety products has contributed to an increase in product complexity that further emphasizes the need for improved scheduling. Proficient scheduling leads to increase in capacity utilization efficiency and hence thereby reducing the time required to complete jobs and consequently increasing the profitability of an organization in present competitive environment. There are different systems of production scheduling including flowshop in which jobs are to be processed through series of machines for optimizing number of required performance measures. In modern manufacturing there is the trend of the development of the Computer Integrated Manufacturing (CIM is computerized integration of the manufacturing activities (Design, Planning, Scheduling and Control)) which produces right product(s) at right time to react quickly to the global competitive market demands. The productivity of CIM is highly depending upon the scheduling of Flexible Manufacturing System (FMS). Machine idle time can be decreased by sorting the makespan which results in the improvement in CIM productivity. Conventional methods of solving scheduling problems based on priority rules still result schedule, sometimes with idle times. To optimize these, this paper models the problem of a flowshop scheduling with the objective of minimizing the makespan. The work proposed here deal with the production planning problem of a flexible manufacturing system. This paper model the problem of a flowshop scheduling with the objective of minimizing the makespan. The objective is to minimize the makespan of batch-processing machines in a flowshop. The processing times and the sizes of the jobs are known and non-identical. The machines can process a batch as long as its capacity is not exceeded. The processing time of a batch is the longest processing time among all the jobs in that batch. The problem under study is non-polynomial (NP)-hard for make span objective. Consequently, comparisons based on RA's heuristics, CDS's heuristics are proposed in this work. Gantt chart is generated to verify the effectiveness of the proposed approaches.
Production scheduling is generally considered to be the one of the most significant issue in the planning and operation of a manufacturing system. Better scheduling system has significant impact on cost reduction, increased productivity, customer satisfaction and overall competitive advantage. In addition, recent customer demand for high variety products has contributed to an increase in product complexity that further emphasizes the need for improved scheduling. Proficient scheduling leads to increase in capacity utilization efficiency and hence thereby reducing the time required to complete jobs and consequently increasing the profitability of an organization in present competitive environment. There are different systems of production scheduling including flowshop in which jobs are to be processed through series of machines for optimizing number of required performance measures. In modern manufacturing there is the trend of the development of the Computer Integrated Manufacturing (CIM is computerized integration of the manufacturing activities (Design, Planning, Scheduling and Control)) which produces right product(s) at right time to react quickly to the global competitive market demands. The productivity of CIM is highly depending upon the scheduling of Flexible Manufacturing System (FMS). Machine idle time can be decreased by sorting the makespan which results in the improvement in CIM productivity. Conventional methods of solving scheduling problems based on priority rules still result schedule, sometimes with idle times. To optimize these, this paper models the problem of a flowshop scheduling with the objective of minimizing the makespan. The work proposed here deal with the production planning problem of a flexible manufacturing system. This paper model the problem of a flowshop scheduling with the objective of minimizing the makespan. The objective is to minimize the makespan of batch-processing machines in a flowshop. The processing times and the sizes of the jobs are known and non-identical. The machines can process a batch as long as its capacity is not exceeded. The processing time of a batch is the longest processing time among all the jobs in that batch. The problem under study is non-polynomial(NP)-hard for makespan objective. Consequently, comparisons based on RA's heuristics, CDS's heuristics are proposed in this work. Gantt chart is generated to verify the effectiveness of the proposed approaches. I. Introduction A Flexible manufacturing system (FMS) consists of a collection of numerically controlled machines with multifunction ability, an automatic material handling system and an online computer network. This network is capable of controlling and directing the whole system. An FMS combines the advantages of a traditional flow line and job-shop systems to meet the changing demands. Thus, it involves many problems, which can be divided into four stages: (a) design, (b) system setup , (c) scheduling and (d) control. FMS Scheduling system is one of the most important information-processing subsystems of CIM system. The productivity of CIM is highly depending upon the quality of FMS scheduling. The basic work of scheduler is to design an optimal FMS schedule according to a certain measure of performance, or scheduling criterion. This work focuses on productivity oriented-makespan criteria. Makespan is the time length from the starting of the first operation of the first demand to the finishing of the last operation of the last demand. The inherent efficiency of a flexible manufacturing system (FMS) combined with additional capabilities, can be harnessed by developing a suitable production plan. Machine scheduling problems arises in diverse areas such as flexible manufacturing system, production planning, computer design, logistics, communication etc. A common feature of many of these problems is that no efficient solution algorithm is known yet for solving it to optimality in polynomial time.
Flowshop Scheduling Problem for 10-Jobs, 10-Machines By Heuristics Models Using Makespan Criterion
In modern manufacturing there is the trend of the development of the Computer Integrated Manufacturing (CIM). CIM is computerized integration of the manufacturing activities (Design, Planning, Scheduling and Control) which produces right product(s) at right time to react quickly to the global competitive market demands. The productivity of CIM is highly depending upon the scheduling of Flexible Manufacturing System (FMS). Machine idle time can be decreased by sorting the make span which results in the improvement in CIM productivity. Conventional methods of solving scheduling problems based on priority rules still result schedule, sometimes with idle times. To optimize these, this paper models the problem of a flowshop scheduling with the objective of minimizing the makespan. The work proposed here deal with the production planning problem of a flexible manufacturing system. This paper models the problem of a flowshop scheduling with the objective of minimizing the make span. The objective is to minimize the makespan of batch-processing machines in a flowshop. The processing times and the sizes of the jobs are known and non-identical. The machines can process a batch as long as its capacity is not exceeded. The processing time of a batch is the longest processing time among all the jobs in that batch. The problem under study is NP-hard for makespan objective. Consequently, comparisons based on Palmer's and Gupta's heuristics are proposed in this work. Gantt chart is generated to verify the effectiveness of the proposed approaches.
Scheduling has to consider operations sequences, machine load and availability of machines. Its aim is to optimize the objectives with the allocation of resources to tasks within the given time periods. A typical flow shop scheduling problem involves the determination of the order of processing of jobs with different processing times over different machines. In reality, any inaccuracy in scheduling can cause long lead-time, production cost increase, and lateness. This inaccuracy may occur due the inaccurate information, uncertainties in demand and uncertainties production facilities. In this paper, matrix manipulation method with MATLAB is proposed to solve flow shop scheduling problem of n jobs on m machines under uncertain processing time. The problems have been considered for comparative analysis with Palmer's heuristic, CDS heuristic & NEH heuristic. The preliminary result indicates that the proposed code is very efficient and time saving in comparison with other methods to find out the minimum makes span through an optimal sequence for flow shop scheduling problem of n jobs on m machines.
Scheduling is one of the most important issues in the planning and operation of manufacturing system, and scheduling has gained much attention increasingly in the recent years. The flexible job shop scheduling problem (JSP) is one of the most difficult problems in this area. It consists of scheduling a set of jobs on a set of machines with the objective to minimize a certain make span time. Each machine is continuously available from time zero, processing one operation at a time without preemption. Each job has a specified processing order on the machine which are fixed and known in advance. Moreover, a processing time is also fixed and known. Different researcher use different algorithms to optimize the make span time. In this paper study has been focused on the different algorithms to optimize the make span time. Now a day's different algorithms that are used are Genetic Algorithm, Artificial Neural Network, Ant Colony Optimization and Particle Swarm Optimization.
A heuristic algorithm for scheduling in a flow shop environment to minimize makespan
Scheduling 'n' jobs on 'm' machines in a flow shop is NP-hard problem and places itself at prominent place in the area of production scheduling. The essence of any scheduling algorithm is to minimize the makespan in a flowshop environment. In this paper an attempt has been made to develop a heuristic algorithm, based on the reduced weightage of machines at each stage to generate different combination of 'm-1' sequences. The proposed heuristic has been tested on several benchmark problems of Taillard (1993) [Taillard, E. (1993). Benchmarks for basic scheduling problems. European Journal of Operational Research, 64, 278-285.]. The performance of the proposed heuristic is compared with three well-known heuristics, namely Palmer's heuristic, Campbell's CDS heuristic, and Dannenbring's rapid access heuristic. Results are evaluated with the best-known upper-bound solutions and found better than the above three.
Flowshop Scheduling Problem for 10-Jobs, 10-Machines By
In modern manufacturing there is the trend of the development of the Computer Integrated Manufacturing (CIM). CIM is computerized integration of the manufacturing activities (Design, Planning, Scheduling and Control) which produces right product(s) at right time to react quickly to the global competitive market demands. The productivity of CIM is highly depending upon the scheduling of Flexible Manufacturing System (FMS). Machine idle time can be decreased by sorting the make span which results in the improvement in CIM productivity. Conventional methods of solving scheduling problems based on priority rules still result schedule, sometimes with idle times. To optimize these, this paper models the problem of a flowshop scheduling with the objective of minimizing the makespan. The work proposed here deal with the production planning problem of a flexible manufacturing system. This paper models the problem of a flowshop scheduling with the objective of minimizing the make span. The objective is to minimize the makespan of batch-processing machines in a flowshop. The processing times and the sizes of the jobs are known and non-identical. The machines can process a batch as long as its capacity is not exceeded. The processing time of a batch is the longest processing time among all the jobs in that batch. The problem under study is NP-hard for makespan objective. Consequently, comparisons based on Palmer's and Gupta's heuristics are proposed in this work. Gantt chart is generated to verify the effectiveness of the proposed approaches.
ICMIEE-PI-14016310 000 Minimization of Makespan in Flow Shop Scheduling Using Heuristics
2014
Production scheduling is one of the most significant issue in production and operations in any manufacturing system that has significant impact on cost reduction and increased productivity. Improper scheduling causes idle time for machines and hampers productivity that may cause an increased price of the product. So the main objective of this study is to minimize the makespan or total completion time. To do this study we have collected our data from Hatil complex limited, Mirpur, Dhaka, Bangladesh. This study presents Palmer’s heuristic, CDS heuristic, NEH algorithm for solving the flow shop scheduling problem to minimize the makespan. NEH yields more elaborate results as compared to Palmer and CDS heuristic. Grant chart is used to verify the effectiveness of heuristics. By applying these three techniques we have gotten an optimal result for each case. The use of these techniques makes it possible to generate a schedule that minimizes the makespan.